iter <- read.csv('iter.txt', header=TRUE, as.is=TRUE)
iter$algorithm <- gsub(" ","",iter$algorithm)
cat_mapping <- data.frame(unique(iter$algorithm), c('biased', 'random', 'sorted', 'sorted', 'random', 'biased', 'biased', 'sorted', 'sorted', 'random', 'biased', 'sorted'), c("#ff943e","#6b00b9", "#c2b802","#eeee2a", "#ff24ff", "#16c0c9", "#25ff18", "#2a7d4c","#fa0000", "#000000", "#bcbcbc", "#439ad6"))
names(cat_mapping) <- c('algorithm', 'category', "color")
iter <- merge(iter, cat_mapping)
df <- iter
for (lengthShort in c(10, 100, 500, 1000, 1000000, 1000000000)){
print(lengthShort)
p = ggplot(subset(df, length == lengthShort), aes(x=amount, y=time, group=algorithm, color=algorithm)) + facet_wrap(~length, scales="free_x", ncol=1)+ scale_x_continuous(trans='log10') + scale_y_continuous(trans='log10') + geom_line(size=1) + theme_bw() + coord_cartesian(ylim=c(1,10000)) + scale_color_manual(values = as.vector(subset(cat_mapping, algorithm %in% unique(subset(df, length == lengthShort)$algorithm))$color))
print(p)
}
## [1] 10
## [1] 100
## [1] 500
## [1] 1000
## [1] 1e+06
## [1] 1e+09
for (lengthShort in c(10, 100, 500, 1000, 1000000, 1000000000)){
print(lengthShort)
p = ggplot(subset(df, length == lengthShort & category=="random"), aes(x=amount, y=time, group=algorithm, color=algorithm)) + facet_wrap(~length, scales="free_x", ncol=1)+ scale_x_continuous(trans='log10') + scale_y_continuous(trans='log10') + geom_line(size=1) + theme_bw()+ coord_cartesian(ylim=c(1,10000)) + scale_color_manual(values = as.vector(subset(cat_mapping, algorithm %in% unique(subset(df, length == lengthShort & category =="random")$algorithm))$color))
print(p)
}
## [1] 10
## [1] 100
## [1] 500
## [1] 1000
## [1] 1e+06
## [1] 1e+09
for (lengthShort in c(10, 100, 500, 1000, 1000000, 1000000000)){
print(lengthShort)
p = ggplot(subset(df, length == lengthShort & category=="sorted"), aes(x=amount, y=time, group=algorithm, color=algorithm)) + facet_wrap(~length, scales="free_x", ncol=1)+ scale_x_continuous(trans='log10') + scale_y_continuous(trans='log10') + geom_line(size=1) + theme_bw()+ coord_cartesian(ylim=c(1,10000)) + scale_color_manual(values = as.vector(subset(cat_mapping, algorithm %in% unique(subset(df, length == lengthShort & category =="sorted")$algorithm))$color))
print(p)
}
## [1] 10
## [1] 100
## [1] 500
## [1] 1000
## [1] 1e+06
## [1] 1e+09
